Refactor reassess_dupes function in reassess_edge.py to improve clarity by introducing local variables for salary, salary_diff, own_diff, and dupes, enhancing readability while maintaining existing logic for ownership adjustments.

global_func/reassess_edge.py

@@ -45,6 +45,12 @@ def calculate_weighted_ownership_single_row(row_ownerships):
     return weighted * 10000
 
 def reassess_dupes(row: pd.Series, salary_max: int) -> float:
+
+    salary = int(row['salary'])
+    salary_diff = int(row['salary_diff'])
+    own_diff = float(row['own_diff'])
+    dupes = int(row['Dupes'])
+
     st.write(f"DEBUG: row['salary'] = {row['salary']}")
     st.write(f"DEBUG: (salary_max - 500) = {salary_max - 500}")
     st.write(f"DEBUG: row['salary'] - (salary_max - 500) = {row['salary'] - (salary_max - 500)}")
@@ -54,12 +60,12 @@ def reassess_dupes(row: pd.Series, salary_max: int) -> float:
     st.write(f"DEBUG: max/100 = {max(0, row['salary'] - (salary_max - 500)) / 100}")
     st.write(f"DEBUG: salary component = {(max(0, row['salary'] - (salary_max - 500)) / 100) * (2 + row['salary_diff'] / 200) * (1 if row['salary_diff'] >= 0 else -1)}")
     return math.ceil(
-        row['Dupes'] + 
+        dupes + 
         (
-            (max(0, (row['salary'] - (salary_max - 500)) / 100) * (2 + (row['salary_diff'] / 200)) * 
-             (1 if row['salary_diff'] >= 0 else -1)) +
+            (max(0, (salary - (salary_max - 500)) / 100) * (2 + (salary_diff / 200)) * 
+             (1 if salary_diff >= 0 else -1)) +
             
-            (row['own_diff'] / 10)
+            (own_diff / 10)
         )
     )